Constrained: p=0.20, reward=5.20, cost=0.60
lambda=0.5: optimal p range [1.00, 1.00]
lambda=1.5: optimal p range [1.00, 1.00]
lambda=2.0: optimal p range [0.00, 1.00]
lambda=3.0: optimal p range [0.00, 0.00]
At constrained optimum, cost-3 episodes occur with probability 0.20
Budget sweep: each extra cost unit buys 2 reward units until budget 3.
At budget 0.6, the expected-cost-optimal policy still exceeds that budget in 20% of episodes.
